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knishioka

Cost Management MCP

by knishioka

aws_costs

Analyze AWS expenditures by service, region, and account to identify optimization opportunities and forecast future costs.

Instructions

Get detailed AWS costs with service breakdown and optimization tips

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startDateYesStart date in YYYY-MM-DD format
endDateYesEnd date in YYYY-MM-DD format
granularityNoCost aggregation granularitydaily
groupByNoDimensions to group costs by
serviceNoFilter by specific AWS service
includeForecastNoInclude cost forecast
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'optimization tips' as an output, which adds some context beyond basic cost retrieval, but fails to address critical aspects like authentication requirements, rate limits, error handling, or whether this is a read-only operation. For a tool with 6 parameters and no annotations, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place by specifying AWS costs, service breakdowns, and optimization tips without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (6 parameters, no output schema, no annotations), the description is incomplete. It doesn't explain the return format, how optimization tips are structured, or prerequisites like AWS account access. For a tool that likely involves financial data and multiple filtering options, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no specific parameter semantics beyond implying cost retrieval with breakdowns and tips. It doesn't explain how parameters like 'groupBy' or 'includeForecast' relate to the described outputs, so it meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get detailed AWS costs with service breakdown and optimization tips.' It specifies the verb ('Get'), resource ('AWS costs'), and additional outputs ('service breakdown and optimization tips'). However, it doesn't explicitly differentiate from sibling tools like 'cost_breakdown' or 'cost_get,' which appear similar.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools like 'cost_breakdown,' 'cost_get,' and 'provider_compare,' there's no indication of when this AWS-specific tool is preferred or what distinguishes it from generic cost tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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